Long-term operation optimization of circulating cooling water systems under fouling conditions

Fouling caused by excess metal ions in hard water can negatively impact the performance of the circulating cooling water system(CCWS)by depositing ions on the heat exchanger's surface.Currently,the operation optimization of CCWS often prioritizes short-term flow velocity optimization for minimizing power consumption,without considering fouling.However,low flow velocity promotes fouling.Therefore,it's crucial to balance fouling and energy/water conservation for optimal CCWS long-term operation.This study proposes a mixed-integer nonlinear programming(MINLP)model to achieve this goal.The model considers fouling in the pipeline,dynamic concentration cycle,and variable frequency drive to optimize the synergy between heat transfer,pressure drop,and fouling.By optimizing the concentration cycle of the CCWS,water conservation and fouling control can be achieved.The model can obtain the optimal operating parameters for different operation intervals,including the number of pumps,frequency,and valve local resistance coefficient.Sensitivity experiments on cycle and environmental temperature reveal that as the cycle increases,the marginal benefits of energy/water conservation decrease.In periods with minimal impact on fouling rate,energy/water conservation can be achieved by increasing the cycle while maintaining a low fouling rate.Overall,the proposed model has significant energy/water saving effects and can comprehensively optimize the CCWS through its incorporation of fouling and cycle optimization.

Using a Computer Driven PID Regulator for Controlling the Vacuum Pump of a Mechanical Milking Machine

Conventional vacuum control in a milking system is accomplished by using a vacuum pump, sized for the maximum air flows into the milking system, running at a full speed. The difference between the pump capacity and the necessary flow of air is compensated by allowing air to enter the system through a regulator. The solution presented in this paper uses a VFD （variable frequency driver） in order to drive the vacuum pump at a controlled speed, so that the air removed equals the air entering the milking system. The VFD technology is able to adjust the rate of air removal from the milking system, by changing the speed of the vacuum pump motor. The VFD is controlled by a computer using a virtual instrument in order to emulate a PID （proportion integration differentiation） regulator. The tests aimed to evaluate the vacuum regulator characteristics and vacuum stability. A statistical analysis of the experimental results was performed and it showed that there was a significant difference between the experimental results obtained for the two methods of vacuum regulation （with vacuum regulator and VFD controller respectively）. The experimental results proved that the used of the VFD controller led to a higher vacuum stability in terms of the error between the set vacuum value and the achieved values.

SVM Algorithm for Vibration Fault Diagnosis in Centrifugal Pump

Vibration failure in the pumping system is a significant issue for indus-tries that rely on the pump as a critical device which requires regular maintenance.To save energy and money,a new automated system must be developed that can detect anomalies at an early stage.This paper presents a case study of a machine learning(ML)-based computational technique for automatic fault detection in a cascade pumping system based on variable frequency drive(VFD).Since the intensity of the vibrational effect depends on which axis has the most significant effect,a three-axis accelerometer is used to measure it in the pumping system.The emphasis is on determining the vibration effect on different axes.For experiment,various ML algorithms are investigated on collected vibratory data through Matlab software in x,y,z axes and performances of the algorithms are compared based on accuracy rate,prediction speed and training time.Based on the proposed research results,the multiclass support vector machine(MSVM)is found to be the best suitable algorithm compared to other algorithms.It has been demonstrated that ML algorithms can detect faults automatically rather than conventional meth-ods.MSVM is used for the proposed work because it is less complex and pro-duces better results with a limited data set.